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Computational Research Scientist (China Energy Group)

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Research/Science
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EA-Energy Analysis Env Impacts
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86060 Requisition #
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Berkeley Lab’s Energy Analysis and Environment Impacts (EAEI) Division has an opening for a Computational Research Scientist to join the China Energy Group!

 

In this role, you will provide technical and scientific leadership, apply engineering and scientific concepts, with an emphasis on research and analyses related to building energy efficiency and distributed energy resources modeling.

 

The China Energy Group (CEG) conducts energy efficiency and clean energy research to solve China’s energy and environmental issues. Over the history of 30 years, the CEG has been working with U.S. Department Of Energy (DOE) as well as scientific research institutes in China to develop impactful, science-based energy and environmental solutions collaboratively with China. The CEG has active research areas in Building Energy Efficiency, Clean Energy and Power Sector, Appliance Energy Efficiency, Low Carbon Eco-city and Industrial Energy Efficiency. The CEG has been actively managing and implementing bi-lateral research programs such as the U.S. China Clean Energy Research Center - Building Energy Efficiency (CERC-BEE), the U.S.-China Eco-Partnership, and the U.S.-China Climate Change Working Group (CCWG).

 

What You Will Do:

  • Develop modeling methodologies to capture China’s building sector long-term energy consumption potentials for national, provincial and city level.

  • Establish distributed energy system models with the focus on district energy planning, optimization and heat waste.

  • Lead or perform policy analysis of building energy efficiency in China focusing on city level best practices and impacts on energy savings and carbon emissions mitigation.

  • Manage the development, implementation, and utilization of software tools for distributed energy system analysis related data collection and synthesis, in support of LBNL research activities.

  • Lead or perform advanced modeling and laboratory testing research in Direct Current (DC) power distribution systems in buildings.

  • Identify funding opportunities and develop proposals while developing and maintaining effective relationships with funders and stakeholders.

  • Author or contribute to conference presentations, project reports, and refereed journal articles. Present results at key scientific conferences.

  • Collaborate with other researchers within and outside of LBNL on research activities.

  • Supervise and advise junior researchers and graduate students research assistants on technical modeling and summarize research findings.

  • Develop project research plans and manage team progress.


What is Required:

  • Ph.D., or equivalent work experience, in Mechanical, Electrical, Industrial Engineering, or related discipline and five years of relevant work experience or equivalent combination of professional, technical and management experience.

  • Demonstrated understanding and experience with building energy simulation and advanced modeling skills by using simulation tools such as EnergyPlus.

  • Demonstrated strong modeling experience of distributed energy optimization and use of optimization software such as GAMS and/or Gurobi to solve distributed energy modeling questions.

  • Demonstrated strong experience of modeling national or city level building sector energy use and assessment of building energy policy impacts on energy savings and carbon emission reduction.

  • Proficient in using macroscopic social sector modeling tools such as LEAP and/or Vensim.

  • Familiarity with building energy efficiency policies in China and its implementation status at central and local levels.

  • Excellent written and oral communication skills.

  • Demonstrated ability to independently carry out creative research with a proven record of publications and achievement.

  • Strong communication skills, both oral and written, in Chinese Mandarin. Proficiency in reviewing Chinese literature.

  • Ability to collaborate effectively with a multidisciplinary team of scientists,  clients and international collaborators.

  • Proven ability to work with multiple principal investigators on several concurring projects and to supervise the activities of others, as needed.

  • Expert knowledge of programming language such as, Python, C++, MATLAB, VBA including experience of using programming language to conduct building energy simulation and energy system optimization research.

  • Extensive knowledge on software engineering project management, design and maintenance of database, servers, developing graphical user interfaces.

  • Able to supervise staff and subcontractors on software developers on database development and software programming.

  • Several years’ experience supervising analytical or technical staff in individual and team-based projects of increasing complexity.

  • Advanced mastery of Excel, proficiency with Word, PowerPoint, and other relevant software tools.

  • Proficiency in various methods of electronic data transfer.

  • Must be available to travel to China to engage stakeholders and present findings.


The posting shall remain open until the position is filled, however for full consideration, please apply by close of business on February 18, 2019.


Notes:

  • This is a full time, M-F, exempt from overtime pay (monthly paid), career appointment.

  • Salary is commensurate with experience.

  • This position may be subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.

  • Work will be primarily performed at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.


Learn About Us:

Berkeley Lab (LBNL) addresses the world’s most urgent scientific challenges by advancing sustainable energy, protecting human health, creating new materials, and revealing the origin and fate of the universe. Founded in 1931, Berkeley Lab’s scientific expertise has been recognized with 13 Nobel prizes. The University of California manages Berkeley Lab for the U.S. Department of Energy’s Office of Science.


Working at Berkeley Lab has many rewards including a competitive compensation program, excellent health and welfare programs, a retirement program that is second to none, and outstanding development opportunities.  To view information about the many rewards that are offered at Berkeley Lab- Click Here.


Equal Employment Opportunity: Berkeley Lab is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status. Berkeley Lab is in compliance with the Pay Transparency Nondiscrimination Provision under 41 CFR 60-1.4.  Click here to view the poster and supplement: "Equal Employment Opportunity is the Law."

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Equal Employment Opportunity: Berkeley Lab is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status. Berkeley Lab is in compliance with the Pay Transparency Nondiscrimination Provision under 41 CFR 60-1.4. Click here to view the poster and supplement: "Equal Employment Opportunity is the Law."

 

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The Lawrence Berkeley National Laboratory provides accommodation to otherwise qualified internal and external applicants who are disabled or become disabled and need assistance with the application process. Internal and external applicants that need such assistance may contact the Lawrence Berkeley National Laboratory to request accommodation by telephone at 510-486-7635, by email to eeoaa@lbl.gov or by U.S. mail at EEO/AA Office, One Cyclotron Road, MS90R-2121, Berkeley, CA 94720. These methods of contact have been put in place ONLY to be used by those internal and external applicants requesting accommodation.